Figure REF  shows distributions of pairwise Jaccard distance conditioned on pairwise relationships. Our proposed kernel based on appearance and geometry (Figure REF , green) generally increases separation between different sibling relationships in comparison to appearance only (Figure REF , orange) as in [1]}. A two-tailed Kolmogorov-Smirnoff (KS) test shows all distributions to be significantly different (\(p-value < 1e-10\) ) except those of DZ and FS siblings sharing approximately 50% of their genes (\(p-value = 0.0199\) ). Furthermore, pairwise KS statistics were all lower for appearance+geometry kernels compared to appearance only, indicating that the geometry kernels lead to increased separation of relationship categories. The Jaccard distance may be rapidly evaluated, and pairs which are outliers from their expected distributions may be easily flagged and inspected for irregularities. For example, the highest Jaccard distance outliers indicated noticeable spatial misalignment between a small number of subject pairs (e.g. Figure REF a. The lowest distance outliers for UR pairs may indicate potential sibling relationships. The blue circles near Figure REF b are pairs involving 3 subjects flagged as UR due to genotyping errors (including a MZ twin) [2]}. Here, nearest neighbor Jaccard distance was used to correctly predict the self-reported families for all three cases, a result confirmed by the HCP.
<FIGURE>